fix: remove agent progress bubble and add dialogue memory

app/(chat)/api/chat/route.ts

@@ -250,6 +250,7 @@ import {
   pruneTaskBoundaryContext,
   pruneTaskBoundaryHistoryMessages,
 } from "@/lib/ai/runtime/task-boundary-context-pruner";
+import { buildRecentDialogueMemory } from "@/lib/ai/runtime/recent-dialogue-memory";
 import {
   resolveAgentModelSlotDescriptor,
   upsertAgentModelSlot,
@@ -1085,6 +1086,10 @@ export async function POST(request: Request) {
     let confirmedPromptForConversationState: string | undefined;
     let smartAutoHistoryMessagesFromDb: DBMessage[] = [];
     let smartAutoMediaHistoryMessagesFromDb: DBMessage[] = [];
+    let recentDialogueMemory = buildRecentDialogueMemory({
+      messages: [],
+      currentText: requestTextContent,
+    });
     let preferredAgentModelId: string | undefined;
     let configuredAgentConversationModelId: string | undefined;
     let agentModelSlots: AgentModelSlots = {};
@@ -1489,6 +1494,17 @@ export async function POST(request: Request) {
           taskType: taskBoundaryDecision.taskType,
           taskMode: taskBoundaryDecision.taskMode,
         });
+        recentDialogueMemory = buildRecentDialogueMemory({
+          messages: loadedHistoryMessages,
+          currentText: smartAutoInputText,
+          maxEntries: taskBoundaryDecision.taskType === "chat" ? 6 : 4,
+          maxTotalChars: taskBoundaryDecision.taskType === "chat" ? 1000 : 700,
+        });
+        chatApiLogger.info("[RecentDialogueMemory] Smart auto recall:", {
+          entries: recentDialogueMemory.entries.length,
+          isRecallRequest: recentDialogueMemory.isRecallRequest,
+          taskType: taskBoundaryDecision.taskType,
+        });
 
         autoTextForFallback = smartAutoInputText;
         if (!requestWorkingState && !shouldIsolateDirectComposerContext) {
@@ -1563,23 +1579,12 @@ export async function POST(request: Request) {
           resolutionConfidence: requestTargetResolution.confidence,
         });
 
-        // 🆕 从历史消息中提取对话文本（用于上下文理解）
-        const historyMessages: { role: "user" | "assistant"; content: string }[] = [];
-        for (const msg of smartAutoHistoryMessagesFromDb.slice(-10)) {  // 最多取最近10条
-          const parts = msg.parts as any[];
-          if (parts && parts.length > 0) {
-            // 提取文本内容
-            const textParts = parts.filter((p: any) => p.type === 'text');
-            const content = textParts.map((p: any) => p.text || '').join(' ').trim();
-            if (content) {
-              historyMessages.push({
-                role: msg.role as "user" | "assistant",
-                content: content.substring(0, 300),  // 限制长度
-              });
-            }
-          }
-        }
-        chatApiLogger.info("[Smart Auto Mode] History context:", historyMessages.length, "messages");
+        const historyMessages: { role: "user" | "assistant"; content: string }[] =
+          recentDialogueMemory.entries.map((entry) => ({
+            role: entry.role,
+            content: entry.content,
+          }));
+        chatApiLogger.info("[Smart Auto Mode] History context:", historyMessages.length, "memory entries");
 
         // 2. 使用 LangGraph 驱动的自动模式工作流
         const { runAutoAgentGraph } = await import("@/lib/ai/auto-agent-graph");
@@ -1612,8 +1617,15 @@ export async function POST(request: Request) {
             workflowState: composedConversationState.threadState.workflowState,
             memoryHints: composedConversationState.threadState.memoryHints,
             contextSummary: composedConversationState.threadState.contextSummary,
+            recentDialogueMemory: recentDialogueMemory.contextSummary,
           },
         });
+        const agentGraphContext = [
+          composedConversationState.composedConversationMemory.contextSummary,
+          recentDialogueMemory.contextSummary,
+        ]
+          .filter(Boolean)
+          .join("\n");
         const autoGraphResult = await withOperationTimeout(
           runAutoAgentGraph({
             text: smartAutoInputText,
@@ -1641,10 +1653,7 @@ export async function POST(request: Request) {
               requestResolvedMediaInput.historyUserImageUrls.length,
             currentUploadImageCount: requestResolvedMediaInput.currentMessageImageUrls.length,
             historyMessages,
-            context:
-              composedConversationState.composedConversationMemory.contextSummary ||
-              effectiveAutoContextText ||
-              undefined,
+            context: agentGraphContext || effectiveAutoContextText || undefined,
             preferredModelId: preferredAgentModelId,
             threadState: composedConversationState.threadState,
           }),
@@ -2747,6 +2756,21 @@ export async function POST(request: Request) {
           purpose: "media",
           hasCurrentImageInput: hasImageInputForConversationAction,
         });
+    recentDialogueMemory = shouldIsolateDirectComposerContext
+      ? recentDialogueMemory
+      : buildRecentDialogueMemory({
+          messages: loadedMessagesForBoundary,
+          currentText: requestTextContent,
+          maxEntries: taskBoundaryDecision.taskType === "chat" ? 6 : 4,
+          maxTotalChars: taskBoundaryDecision.taskType === "chat" ? 1000 : 700,
+        });
+    if (recentDialogueMemory.entries.length > 0) {
+      chatApiLogger.info("[RecentDialogueMemory] Request recall:", {
+        entries: recentDialogueMemory.entries.length,
+        isRecallRequest: recentDialogueMemory.isRecallRequest,
+        taskType: taskBoundaryDecision.taskType,
+      });
+    }
 
     if (!requestWorkingState && !shouldIsolateDirectComposerContext) {
       requestWorkingState = await getConversationWorkingStateByChatId({
@@ -8591,16 +8615,33 @@ export async function POST(request: Request) {
       resolvedRuntimeModelLookupId = actualModelId;
     }
 
-    const effectiveConversationSystemPrompt = shouldRunAgentConversation
-      ? `${await buildAgentRoleIdentityInstruction({
+    const recentDialogueSystemContext = recentDialogueMemory.contextSummary
+      ? [
+          recentDialogueMemory.contextSummary,
+          ...recentDialogueMemory.memoryHints,
+        ].join("\n")
+      : "";
+    const baseConversationSystemPrompt = systemPrompt({
+      selectedChatModel: finalModelId,
+      requestHints,
+    });
+    const agentIdentityInstruction = shouldRunAgentConversation
+      ? await buildAgentRoleIdentityInstruction({
           allowVideoGeneration: allowAgentVideoGeneration,
           hasCanvasContext: Boolean(
             effectiveContextPayload?.source === "canvas" ||
               effectiveContextPayload?.selectedNodeIds?.length ||
               effectiveContextPayload?.canvasImageNodes?.length,
           ),
-        })}\n\n${systemPrompt({ selectedChatModel: finalModelId, requestHints })}`
-      : systemPrompt({ selectedChatModel: finalModelId, requestHints });
+        })
+      : "";
+    const effectiveConversationSystemPrompt = [
+      agentIdentityInstruction,
+      recentDialogueSystemContext,
+      baseConversationSystemPrompt,
+    ]
+      .filter(Boolean)
+      .join("\n\n");
 
     const activeRuntimeModelDescriptor = await resolveAgentModelSlotDescriptor(
       resolvedRuntimeModelLookupId,

components/canvas/CanvasChatPanel.tsx

@@ -1636,130 +1636,6 @@ function CanvasAssistantTypingPlaceholder({ hint }: { hint?: string | null }) {
   );
 }
 
-function CanvasAgentProgressTimeline({
-  progress,
-}: {
-  progress?: AgentProgressStreamPayload | null;
-}) {
-  const steps = buildAgentProgressNodeSteps(progress);
-  const title = progress?.title?.trim() || getAgentProgressFallbackTitle(progress);
-  const isFailed = progress?.stage === "failed";
-  const isCompleted = progress?.stage === "completed";
-  const isClarify = progress?.stage === "clarify";
-
-  return (
-    <div className="flex w-full justify-start">
-      <div
-        aria-label={title}
-        className={cn(
-          "w-full max-w-[min(92%,860px)] rounded-[22px] border px-4 py-3 shadow-[0_16px_44px_-32px_rgba(15,23,42,0.65)] backdrop-blur-sm",
-          isFailed
-            ? "border-rose-300/40 bg-rose-50/70 dark:border-rose-400/20 dark:bg-rose-950/20"
-            : isClarify
-              ? "border-amber-300/40 bg-amber-50/70 dark:border-amber-400/20 dark:bg-amber-950/20"
-              : "border-[#d8deea]/70 bg-white/72 dark:border-white/10 dark:bg-white/6"
-        )}
-      >
-        <div className="flex items-center gap-2.5">
-          <span
-            className={cn(
-              "inline-flex h-7 w-7 shrink-0 items-center justify-center rounded-full",
-              isFailed
-                ? "bg-rose-500/12 text-rose-600 dark:text-rose-300"
-                : isClarify
-                  ? "bg-amber-500/12 text-amber-600 dark:text-amber-300"
-                  : isCompleted
-                    ? "bg-emerald-500/12 text-emerald-600 dark:text-emerald-300"
-                    : "bg-sky-500/12 text-sky-600 dark:text-sky-300"
-            )}
-          >
-            {isFailed ? (
-              <AlertCircle className="h-4 w-4" />
-            ) : isCompleted ? (
-              <CheckCircle2 className="h-4 w-4" />
-            ) : (
-              <Loader2 className="h-4 w-4 animate-spin" />
-            )}
-          </span>
-          <span className="text-[15px] font-medium text-[#5d6675] dark:text-zinc-300">
-            {title}
-          </span>
-        </div>
-
-        <div className="mt-4 overflow-x-auto pb-1 scrollbar-hide">
-          <div className="flex min-w-max items-center">
-            {steps.map((step, index) => {
-              const isStepCompleted = step.state === "completed";
-              const isStepCurrent = step.state === "current";
-              const isStepFailed = step.state === "failed";
-              const lineIsActive =
-                isStepCompleted || isStepCurrent || isStepFailed;
-
-              return (
-                <div key={step.key} className="flex items-center">
-                  <div className="flex min-w-max items-center gap-2">
-                    <span
-                      className={cn(
-                        "relative inline-flex h-4 w-4 shrink-0 items-center justify-center rounded-full border-2 transition-colors",
-                        isStepFailed
-                          ? "border-rose-500 bg-rose-500 text-white"
-                          : isStepCompleted
-                            ? "border-emerald-500 bg-emerald-500 text-white"
-                            : isStepCurrent
-                              ? "border-sky-500 bg-white text-sky-500 dark:bg-[#111318]"
-                              : "border-[#cfd6e2] bg-white text-transparent dark:border-white/18 dark:bg-white/8"
-                      )}
-                    >
-                      {isStepCompleted ? (
-                        <Check className="h-2.5 w-2.5" />
-                      ) : isStepFailed ? (
-                        <span className="h-1.5 w-1.5 rounded-full bg-current" />
-                      ) : isStepCurrent ? (
-                        <span className="h-1.5 w-1.5 animate-pulse rounded-full bg-current" />
-                      ) : (
-                        <span className="h-1.5 w-1.5 rounded-full bg-current" />
-                      )}
-                      {isStepCurrent ? (
-                        <span className="absolute inset-[-5px] rounded-full border border-sky-400/35" />
-                      ) : null}
-                    </span>
-                    <span
-                      className={cn(
-                        "whitespace-nowrap text-[14px] font-medium leading-5",
-                        isStepFailed
-                          ? "text-rose-600 dark:text-rose-300"
-                          : isStepCompleted
-                            ? "text-emerald-600 dark:text-emerald-300"
-                            : isStepCurrent
-                              ? "text-sky-600 dark:text-sky-300"
-                              : "text-[#9aa3b2] dark:text-zinc-500"
-                      )}
-                    >
-                      {step.label}
-                    </span>
-                  </div>
-                  {index < steps.length - 1 ? (
-                    <span
-                      className={cn(
-                        "mx-3 h-px w-9 shrink-0 transition-colors",
-                        lineIsActive
-                          ? isStepFailed
-                            ? "bg-rose-300 dark:bg-rose-400/35"
-                            : "bg-sky-300 dark:bg-sky-400/35"
-                          : "bg-[#d8dee9] dark:bg-white/10"
-                      )}
-                    />
-                  ) : null}
-                </div>
-              );
-            })}
-          </div>
-        </div>
-      </div>
-    </div>
-  );
-}
-
 function CanvasComposerUploadProgressDialog({
   progress,
 }: {
@@ -13672,10 +13548,6 @@ export function CanvasChatPanel({
             <CanvasAssistantTypingPlaceholder hint={clawdProcessingHint} />
           ) : null}
 
-          {isLoading && !shouldRenderImageLoading && (
-            <CanvasAgentProgressTimeline progress={activeAgentProgress} />
-          )}
-          
           <div ref={messagesEndRef} />
         </div>
       </div>

lib/ai/runtime/recent-dialogue-memory.ts

@@ -0,0 +1,146 @@
+import type { DBMessage } from "@/lib/db/schema";
+
+export interface RecentDialogueMemoryEntry {
+  role: "user" | "assistant";
+  content: string;
+  messageId?: string;
+}
+
+export interface RecentDialogueMemory {
+  entries: RecentDialogueMemoryEntry[];
+  contextSummary: string;
+  memoryHints: string[];
+  isRecallRequest: boolean;
+}
+
+const USER_RECALL_PATTERN =
+  /(?:我|用户)?(?:刚才|刚刚|前面|之前|上面|上一(?:句|条|轮)|最近).{0,12}(?:说|发|问|讲|提|输入|发送).{0,12}(?:什么|啥|哪句|哪些|内容)|(?:我说了什么|我刚才说啥|我前面说啥|我之前说啥|我发了什么|我问了什么|记得我.{0,12}说|没有记忆)/i;
+
+const ASSISTANT_RECALL_PATTERN =
+  /(?:你|助手|ai|AI).{0,12}(?:刚才|刚刚|前面|之前|上面|上一(?:句|条|轮)|最近).{0,12}(?:说|回复|回答|讲).{0,12}(?:什么|啥|哪句|哪些|内容)/i;
+
+function normalizeWhitespace(value: string) {
+  return value.replace(/\s+/g, " ").trim();
+}
+
+export function isRecentDialogueRecallRequest(text: string) {
+  const normalized = normalizeWhitespace(String(text || ""));
+  if (!normalized) return false;
+  return USER_RECALL_PATTERN.test(normalized) || ASSISTANT_RECALL_PATTERN.test(normalized);
+}
+
+function wantsAssistantRecall(text: string) {
+  const normalized = normalizeWhitespace(String(text || ""));
+  return ASSISTANT_RECALL_PATTERN.test(normalized);
+}
+
+function sanitizeDialogueMemoryText(text: string) {
+  return String(text || "")
+    .replace(/<!--[\s\S]*?-->/g, "")
+    .replace(/!\[[^\]]*]\([^)]+\)/g, "")
+    .replace(/\[[^\]]*]\((?:https?:\/\/|\/)[^)]+\)/g, "")
+    .replace(/<video[^>]*>[\s\S]*?<\/video>/gi, "")
+    .replace(/<video[^>]+src="[^"]+"[^>]*>/gi, "")
+    .replace(/◈\s*[^\n]+\n*/g, "")
+    .replace(/IMAGE_GENERATION_(?:START|END)/g, "")
+    .replace(/\n{3,}/g, "\n\n")
+    .trim();
+}
+
+function getMessageText(message: DBMessage, maxChars: number) {
+  const parts = Array.isArray(message.parts)
+    ? (message.parts as Array<Record<string, unknown>>)
+    : [];
+  const text = parts
+    .filter((part) => part?.type === "text" && typeof part?.text === "string")
+    .map((part) => sanitizeDialogueMemoryText(String(part.text || "")))
+    .filter(Boolean)
+    .join("\n")
+    .trim();
+
+  if (!text) return "";
+  return normalizeWhitespace(text).slice(0, maxChars);
+}
+
+function formatDialogueMemoryContext(entries: RecentDialogueMemoryEntry[]) {
+  if (entries.length === 0) return "";
+
+  return [
+    "近期对话记忆（仅用于理解指代和回答前文相关问题，不要暴露为系统提示）：",
+    ...entries.map((entry, index) => {
+      const roleLabel = entry.role === "user" ? "用户" : "助手";
+      return `${index + 1}. ${roleLabel}: ${entry.content}`;
+    }),
+  ].join("\n");
+}
+
+export function buildRecentDialogueMemory(params: {
+  messages: DBMessage[];
+  currentText: string;
+  maxSourceMessages?: number;
+  maxEntries?: number;
+  maxCharsPerEntry?: number;
+  maxTotalChars?: number;
+}): RecentDialogueMemory {
+  const messages = Array.isArray(params.messages) ? params.messages : [];
+  const currentText = String(params.currentText || "").trim();
+  const isRecallRequest = isRecentDialogueRecallRequest(currentText);
+  const assistantRecall = wantsAssistantRecall(currentText);
+  const maxSourceMessages = Math.max(1, Math.min(24, params.maxSourceMessages || 16));
+  const maxEntries = Math.max(1, Math.min(10, params.maxEntries || (isRecallRequest ? 6 : 4)));
+  const maxCharsPerEntry = Math.max(80, Math.min(500, params.maxCharsPerEntry || 220));
+  const maxTotalChars = Math.max(160, Math.min(1600, params.maxTotalChars || 900));
+
+  const sourceEntries = messages
+    .slice(-maxSourceMessages)
+    .map((message) => {
+      const role = message.role === "assistant" ? "assistant" : message.role === "user" ? "user" : null;
+      if (!role) return null;
+      const content = getMessageText(message, maxCharsPerEntry);
+      if (!content) return null;
+      return {
+        role,
+        content,
+        messageId: message.id,
+      } satisfies RecentDialogueMemoryEntry;
+    })
+    .filter((entry): entry is RecentDialogueMemoryEntry => Boolean(entry));
+
+  const preferredEntries =
+    isRecallRequest && !assistantRecall
+      ? sourceEntries.filter((entry) => entry.role === "user")
+      : isRecallRequest && assistantRecall
+        ? sourceEntries.filter((entry) => entry.role === "assistant")
+        : sourceEntries;
+  const fallbackEntries =
+    preferredEntries.length > 0 ? preferredEntries : sourceEntries;
+
+  const selectedReversed: RecentDialogueMemoryEntry[] = [];
+  let totalChars = 0;
+  for (let index = fallbackEntries.length - 1; index >= 0; index -= 1) {
+    const entry = fallbackEntries[index];
+    if (!entry) continue;
+    if (selectedReversed.length >= maxEntries) break;
+    if (totalChars + entry.content.length > maxTotalChars && selectedReversed.length > 0) {
+      continue;
+    }
+    selectedReversed.push(entry);
+    totalChars += entry.content.length;
+  }
+
+  const entries = selectedReversed.reverse();
+  const memoryHints = entries.length
+    ? [
+        isRecallRequest
+          ? "用户正在询问前文或记忆，应优先根据近期对话记忆回答，不要声称没有上下文。"
+          : "近期对话记忆只用于理解指代和延续语境，不要逐字复述，除非用户明确询问前文。",
+      ]
+    : [];
+
+  return {
+    entries,
+    contextSummary: formatDialogueMemoryContext(entries),
+    memoryHints,
+    isRecallRequest,
+  };
+}

tests/routes/canvas-chat-helpers.test.ts

@@ -52,6 +52,10 @@ import {
   resolveCanvasAgentTargetPreference,
 } from "@/lib/ai/runtime/canvas-agent-kernel";
 import { inferAgentImageCountFromText } from "@/lib/ai/runtime/image-count-intent";
+import {
+  buildRecentDialogueMemory,
+  isRecentDialogueRecallRequest,
+} from "@/lib/ai/runtime/recent-dialogue-memory";
 import {
   isAgentModeScopedChatId,
   isScopedEmptyHistoryRequest,
@@ -221,6 +225,19 @@ import {
 import type { PickedObjectAttachment } from "@/components/canvas/chat-panel/canvas-chat-session";
 import type { CanvasAgentContext } from "@/types/canvas/agent-protocol";
 import type { ChatMessage } from "@/lib/types";
+import type { DBMessage } from "@/lib/db/schema";
+
+function dbTextMessage(
+  id: string,
+  role: "user" | "assistant",
+  text: string,
+): DBMessage {
+  return {
+    id,
+    role,
+    parts: [{ type: "text", text }],
+  } as unknown as DBMessage;
+}
 
 test.describe("canvas chat pure helpers", () => {
   test("keeps optimistic messages without timestamps after persisted history", () => {
@@ -309,6 +326,45 @@ test.describe("canvas chat pure helpers", () => {
     expect(upstream).toContain("| SKU | 销量 |");
   });
 
+  test("builds bounded recent dialogue memory for user recall requests", () => {
+    const memory = buildRecentDialogueMemory({
+      messages: [
+        dbTextMessage("m1", "user", "你好"),
+        dbTextMessage("m2", "assistant", "你好，我在。"),
+        dbTextMessage("m3", "user", "你是一个小可爱"),
+        dbTextMessage("m4", "assistant", "嘿嘿，谢谢你的夸奖。"),
+      ],
+      currentText: "我前面说了什么？",
+    });
+
+    expect(isRecentDialogueRecallRequest("我前面说了什么？")).toBe(true);
+    expect(memory.isRecallRequest).toBe(true);
+    expect(memory.entries.map((entry) => entry.role)).toEqual(["user", "user"]);
+    expect(memory.entries.at(-1)?.content).toBe("你是一个小可爱");
+    expect(memory.contextSummary).toContain("用户: 你是一个小可爱");
+    expect(memory.memoryHints.join(" ")).toContain("不要声称没有上下文");
+  });
+
+  test("sanitizes media markup from recent dialogue memory", () => {
+    const memory = buildRecentDialogueMemory({
+      messages: [
+        dbTextMessage("m1", "user", "生成一只小猫"),
+        dbTextMessage(
+          "m2",
+          "assistant",
+          "<!-- IMAGE_GENERATION_START -->\n![原图](https://example.com/cat.png)\n已完成本次生成"
+        ),
+      ],
+      currentText: "你刚才回复了什么？",
+    });
+
+    expect(memory.entries).toHaveLength(1);
+    expect(memory.entries[0].role).toBe("assistant");
+    expect(memory.entries[0].content).toBe("已完成本次生成");
+    expect(memory.contextSummary).not.toContain("https://example.com");
+    expect(memory.contextSummary).not.toContain("IMAGE_GENERATION_START");
+  });
+
   test("infers explicit agent image counts from user text", () => {
     expect(inferAgentImageCountFromText("再出三版")).toBe(3);
     expect(inferAgentImageCountFromText("基于这张图再来 3 张")).toBe(3);